The type to use for the index.
The type to use for each value.
Get an iterator to enumerate the values of the series.
Enumerating the iterator forces lazy evaluation to complete.
This function is automatically called by for...of
.
An iterator for the values in the series.
Gets a new series containing all values after the specified index value (exclusive).
The index value after which to start the new series.
Returns a new series containing all values after the specified index value.
Reduces the values in the series to a single result.
aggregate
is similar to Series.reduce, but the parameters are reversed.
Please use Series.reduce in preference to aggregate
.
Returns a new value that has been reduced from the input series by passing it through the 'reducer' function.
Evaluates a predicate function for every value in the series to determine if some condition is true/truthy for all values in the series.
Predicate function that receives each value. It should returns true/truthy for a match, otherwise false/falsy.
Returns true if the predicate has returned true or truthy for every value in the series, otherwise returns false. Returns false for an empty series.
Compute the amount of change between pairs or sets of values in the series.
Optional period for computing the change - defaults to 2.
Sets which side of the window the index comes from: start or end. Can be "start" or "end", defaults to "end".
Returns a new series where each value indicates the amount of change from the previous number value in the original series.
Compute the absolute range of values in each period. The range for each period is the absolute difference between largest (max) and smallest (min) values in that period.
Period for computing the range.
Sets which side of the window the index comes from: start or end. Can be "start" or "end", defaults to "end".
Returns a new series where each value indicates the absolute range of values for each period in the original series.
Evaluates a predicate function for every value in the series to determine if some condition is true/truthy for any of values in the series.
If no predicate is specified then it simply checks if the series contains more than zero values.
Optional predicate function that receives each value. It should return true/truthy for a match, otherwise false/falsy.
Returns true if the predicate has returned truthy for any value in the series, otherwise returns false. If no predicate is passed it returns true if the series contains any values at all. Returns false for an empty series.
Append a pair to the end of a series. Doesn't modify the original series! The returned series is entirely new and contains values from the original series plus the appended pair.
The index/value pair to append.
Returns a new series with the specified pair appended.
Get the value, if there is one, with the specified index.
Index to for which to retreive the value.
Returns the value from the specified index in the series or undefined if there is no such index in the present in the series.
Average the values in a series and returns the result.
average
is an alias of Series.mean.
Returns the average of the number values in the series.
Forces lazy evaluation to complete and 'bakes' the series into memory.
Returns a series that has been 'baked', all lazy evaluation has completed.
Gets a new series containing all values up to the specified index value (exclusive).
The index value at which to end the new series.
Returns a new series containing all values up to (but not including) the specified index value.
Gets a new series containing all values between the specified index values (inclusive).
The index at which to start the new series.
The index at which to end the new series.
Returns a new series containing all values between the specified index values (inclusive).
Organise all values in the series into the specified number of buckets. Assumes that the series is a series of numbers.
WARNING: This function is deprecated and will be removed in the future.
The number of buckets to create.
Returns a dataframe containing bucketed values. The input values are divided up into these buckets.
Cast the value of the series to a new type. This operation has no effect but to retype the values that the series contains.
The same series, but with the type changed.
Concatenate multiple other series onto this series.
Multiple arguments. Each can be either a series or an array of series.
Returns a single series concatenated from multiple input series.
Count the number of values in the seriese
Returns the count of all values.
Counts the number of sequential values where the predicate evaluates to truthy. Outputs 0 for values when the predicate evaluates to falsy.
User-defined function. Should evaluate to truthy to activate the counter or falsy to deactivate it.
Returns a new series that counts up the number of sequential values where the predicate evaluates to truthy. 0 values appear when the prediate evaluates to falsy.
Generates a cumulative sum across a series.
Returns a new series that is the cumulative sum of values across the input series.
Detect the the frequency of the types of the values in the series. This is a good way to understand the shape of your data.
Returns a DataFrame with rows that confirm to ITypeFrequency that describes the data types contained in the original series.
Detect the frequency of the values in the series. This is a good way to understand the shape of your data.
Returns a DataFrame with rows that conform to IValueFrequency that describes the values contained in the original series.
Returns only the set of values in the series that are distinct. Provide a user-defined t (tor to specify criteria for determining the distinctness. This can be used to remove duplicate values from the series.
Optional user-defined selector function that specifies the criteria used to make comparisons for duplicate values.
Returns a series containing only unique values in the series.
Gets a new series containing all values up until and including the specified index value (inclusive).
The index value at which to end the new series.
Returns a new series containing all values up until and including the specified index value.
Creates a new series by merging two input series. The resulting series contains only the values from the 1st series that don't appear in the 2nd series. This is essentially subtracting the values from the 2nd series from the 1st and creating a new series with the remaining values.
The inner series to merge (the series you call the function on is the 'outer' series).
Optional user-defined selector function that selects the key from the outer series that is used to match the two series.
Optional user-defined selector function that selects the key from the inner series that is used to match the two series.
Returns a new series that contains only the values from the 1st series that don't appear in the 2nd series.
Fill gaps in a series.
User-defined comparer function that is passed pairA and pairB, two consecutive values, return truthy if there is a gap between the value, or falsey if there is no gap.
User-defined generator function that is passed pairA and pairB, two consecutive values, returns an array of pairs that fills the gap between the values.
Returns a new series with gaps filled in.
Filter the series through a user-defined predicate function.
This is the same concept as the JavaScript function Array.filter
but filters a data series rather than an array.
Predicate function to filter values from the series. Returns true/truthy to keep elements, or false/falsy to omit elements.
Returns a new series containing only the values from the original series that matched the predicate.
Get the first value of the series.
Returns the first value of the series.
Transforms and flattens an input series, generating a new series. The transformer function is called for each value in the input series and produces an array that is then flattened into the generated series.
This is the same concept as the JavaScript function Array.flatMap
but maps over a data series rather than an array.
A user-defined function that transforms each value into an array that is then flattened into the generated series.
Returns a new series generated by calling the transformer function over each element of the input.
Invoke a callback function for each value in the series.
The calback function to invoke for each value.
Returns the original series with no modifications.
Counts frequencies in the series to produce a frequency table.
Options for computing the frequency table (e.g. numGroups
which defaults to 10).
Returns a dataframe for the frequency table showing the frequency for the band of values in each group.
Collects values in the series into a new series of groups according to a user-defined selector function.
User-defined selector function that specifies the criteriay to group by.
Returns a new series of groups. Each group is a series with values that have been grouped by the 'selector' function.
Collects values in the series into a new series of groups based on if the values are the same or according to a user-defined selector function.
Optional selector that specifies the criteria for grouping.
Returns a new series of groups. Each group is a series with values that are the same or have been grouped by the 'selector' function.
Get X value from the start of the series. Pass in a negative value to get all values at the head except for X values at the tail.
Number of values to take.
Returns a new series that has only the specified number of values taken from the start of the original series.
Converts (inflates) a series to a DataFrame.
Optional user-defined selector function that transforms each value to produce the dataframe.
Returns a dataframe that was created from the original series.
Insert a pair at the start of the series. Doesn't modify the original series! The returned series is entirely new and contains values from the original series plus the inserted pair.
The index/value pair to insert.
Returns a new series with the specified pair inserted.
Creates a new series by merging two input series. The resulting series contains the intersection of values from the two input series. These are only the values that appear in both series.
The inner series to merge (the series you call the function on is the 'outer' series).
Optional user-defined selector function that selects the key from the outer series that is used to match the two series.
Optional user-defined selector function that selects the key from the inner series that is used to match the two series.
Returns a new series that contains the intersection of values from the two input series.
Invert the sign of every number value in the series. This assumes that the input series contains numbers.
Returns a new series with all number values inverted.
Creates a new series by merging two input series. The resulting dataframe contains only those value that have matching keys in both input series.
The 'inner' series to join (the series you are callling the function on is the 'outer' series).
User-defined selector function that chooses the join key from the outer series.
User-defined selector function that chooses the join key from the inner series.
User-defined function that merges outer and inner values.
Returns the new merged series.
Creates a new series by merging two input series. The resulting series contains only those values that are only present in one or the other of the series, not both.
The 'inner' series to join (the series you are callling the function on is the 'outer' series).
User-defined selector function that chooses the join key from the outer series.
User-defined selector function that chooses the join key from the inner series.
User-defined function that merges outer and inner values.
Implementation from here:
http://blogs.geniuscode.net/RyanDHatch/?p=116
Returns the new merged series.
Creates a new series by merging two input series. The resulting series contains only those values that are present either in both series or only in the outer (left) series.
The 'inner' series to join (the series you are callling the function on is the 'outer' series).
User-defined selector function that chooses the join key from the outer series.
User-defined selector function that chooses the join key from the inner series.
User-defined function that merges outer and inner values.
Implementation from here:
http://blogs.geniuscode.net/RyanDHatch/?p=116
Returns the new merged series.
Creates a new series by merging two input series. The resulting series contains only those values that are present either in both series or only in the inner (right) series.
The 'inner' series to join (the series you are callling the function on is the 'outer' series).
User-defined selector function that chooses the join key from the outer series.
User-defined selector function that chooses the join key from the inner series.
User-defined function that merges outer and inner values.
Implementation from here:
http://blogs.geniuscode.net/RyanDHatch/?p=116
Returns the new merged series.
Get the last value of the series.
Returns the last value of the series.
Transforms an input series, generating a new series. The transformer function is called for each element of the input and the collection of outputs creates the generated series.
This is the same concept as the JavaScript function Array.map
but maps over a data series rather than an array.
A user-defined transformer function that transforms each element from the input to generate the output.
Returns a new series generated by calling the transformer function over each element of the input.
Get the max value in the series.
Returns the maximum of the number values in the series.
Computes and returns the mean value of a set of values.
Returns the mean of the number values in the series.
Get the median value in the series. Note that this sorts the series, which can be expensive.
Returns the median of the values in the series.
Merge one or more series into this series. Values are merged by index. Values at each index are combined into arrays in the resulting series.
The merged series.
Get the min value in the series.
Returns the minimum of the number values in the series.
Get the mode of the values in the series. The mode is the most frequent value in the series. Note that this reads the entire series into memory, which can be expensive.
Returns the mode of the values in the series.
Evaluates a predicate function for every value in the series to determine if some condition is true/truthy for none of values in the series.
If no predicate is specified then it simply checks if the series contains zero values.
Optional predicate function that receives each value. It should return true/truthy for a match, otherwise false/falsy.
Returns true if the predicate has returned truthy for zero values in the series, otherwise returns false. Returns false for an empty series.
Sorts the series in ascending order by a value defined by the user-defined selector function.
User-defined selector function that selects the value to sort by.
Returns a new series that has been ordered accorrding to the value chosen by the selector function.
Sorts the series in descending order by a value defined by the user-defined selector function.
User-defined selector function that selects the value to sort by.
Returns a new series that has been ordered accorrding to the value chosen by the selector function.
Parse a series with string values and convert it to a series with date values.
Optional formatting string for dates.
Moment is used for date parsing. https://momentjs.com
Returns a new series with values parsed from strings to dates.
Parse a series with string values and convert it to a series with float values.
Returns a new series with values parsed from strings to floats.
Parse a series with string values and convert it to a series with int values.
Returns a new series with values parsed from strings to ints.
Compute the percentage change between pairs or sets of values in the series. Percentages are expressed as 0-100 values.
Optional period for computing the percentage - defaults to 2.
Sets which side of the window the index comes from: start or end. Can be "start" or "end", defaults to "end".
Returns a new series where each value indicates the percent change from the previous number value in the original series.
Compute the range of values in each period in proportion to the latest value. The range for each period is the absolute difference between largest (max) and smallest (min) values in that period. Proportions are expressed as 0-1 values.
Period for computing the range.
Sets which side of the window the index comes from: start or end. Can be "start" or "end", defaults to "end".
Returns a new series where each value indicates the proportion change from the previous number value in the original series.
For each period, compute the percent of values that are less than the last value in the period. Percent are expressed as 0-100 values.
Optional period for computing the percent rank - defaults to 2.
Returns a new series where each value indicates the percent rank value for that period.
Compute the proportion change between pairs or sets of values in the series. Proportions are expressed as 0-1 values.
Optional period for computing the proportion - defaults to 2.
Sets which side of the window the index comes from: start or end. Can be "start" or "end", defaults to "end".
Returns a new series where each value indicates the proportion change from the previous number value in the original series.
Compute the range of values in each period in proportion to the latest value. The range for each period is the absolute difference between largest (max) and smallest (min) values in that period. Proportions are expressed as 0-1 values.
Period for computing the range.
Sets which side of the window the index comes from: start or end. Can be "start" or "end", defaults to "end".
Returns a new series where each value indicates the proportion change from the previous number value in the original series.
For each period, compute the proportion of values that are less than the last value in the period. Proportions are expressed as 0-1 values.
Optional period for computing the proportion rank - defaults to 2.
Returns a new series where each value indicates the proportion rank value for that period.
Get the range of values in the series.
Returns the range of the number values in the series.
Reduces the values in the series to a single result.
This is the same concept as the JavaScript function Array.reduce
but reduces a data series rather than an array.
Function that takes the seed and then each value in the series and produces the reduced value.
Optional initial value, if not specifed the first value in the series is used as the initial value.
Returns a new value that has been reduced from the input series by passing it through the 'reducer' function.
Gets a new series in reverse order.
Returns a new series that is the reverse of the original.
Partition a series into a new series of rolling data windows. Each value in the new series is a rolling chunk of data from the original series.
The number of data values to include in each data window.
Sets which side of the window the index comes from: start or end. Can be "start" or "end", defaults to "end".
Returns a new series, each value of which is a rolling chunk of the original series.
Produces a new series with all number values rounded to the specified number of places.
The number of decimal places, defaults to 2.
Returns a new series with all number values rounded to the specified number of places.
Standardize a series of numbers by converting each "standard deviations from the mean". This converts the input series to Z scores using the sample standard deviation.
A new series containing Z scores computed from the input series.
Get the (sample) standard deviation of number values in the series.
Returns the (sample) standard deviation of the values in the series.
Get the (sample) variance of number values in the series.
Returns the (sample) variance of the values in the series.
Transforms an input series, generating a new series. The transformer function is called for each element of the input and the collection of outputs creates the generated series.
select
is an alias for Series.map.
This is the same concept as the JavaScript function Array.map
but maps over a data series rather than an array.
A user-defined transformer function that transforms each element from the input to generate the output.
Returns the series generated by calling the transformer function over each value in the input series.
Transforms and flattens an input series, generating a new series. The transformer function is called for each value in the input series and produces an array that is then flattened into the generated series.
selectMany
is an alias for Series.flatMap.
This is the same concept as the JavaScript function Array.flatMap
but maps over a data series rather than an array.
A user-defined function that transforms each value into an array that is then flattened into the generated series.
Returns a new series generated by calling the transformer function over each element of the input.
Eliminates adjacent duplicate values.
For each group of adjacent values that are equivalent only returns the last index/row for the group, thus ajacent equivalent values are collapsed down to the last value.
Optional selector function to determine the value used to compare for equivalence.
Returns a new series with groups of adjacent duplicate vlaues collapsed to a single value per group.
Skip a number of values in the series.
Number of values to skip.
Returns a new series with the specified number of values skipped.
Skips values in the series untils a condition evaluates to true or truthy.
Return true/truthy to stop skipping values in the original series.
Returns a new series with all initial sequential values removed until the predicate returned true/truthy.
Skips values in the series while a condition evaluates to true or truthy.
Returns true/truthy to continue to skip values in the original series.
Returns a new series with all initial sequential values removed while the predicate returned true/truthy.
Standardize a series of numbers by converting each "standard deviations from the mean". This converts the input series to Z scores using the population standard deviation.
A new series containing Z scores computed from the input series.
Gets a new series containing all values starting at or after the specified index value.
The index value at which to start the new series.
Returns a new series containing all values starting at or after the specified index value.
Get the standard deviation of number values in the series.
Returns the standard deviation of the values in the series.
Sum the values in a series and returns the result.
Returns the sum of the number values in the series.
Get X values from the end of the series. Pass in a negative value to get all values at the tail except X values at the head.
Number of values to take.
Returns a new series that has only the specified number of values taken from the end of the original series.
Take a number of values from the series.
Returns a new series with only the specified number of values taken from the original series.
Takes values from the series until a condition evaluates to true or truthy.
Return true/truthy to stop taking values in the original series.
Returns a new series with only the initial sequential values taken until the predicate returned true/truthy.
Takes values from the series while a condition evaluates to true or truthy.
Returns true/truthy to continue to take values from the original series.
Returns a new series with only the initial sequential values that were taken while the predicate returned true/truthy.
Extract values from the series as an array. This forces lazy evaluation to complete.
Returns an array of the values contained within the series.
Convert the series to a JavaScript object.
User-defined selector function that selects keys for the resulting object.
User-defined selector function that selects values for the resulting object.
Returns a JavaScript object generated from the series by applying the key and value selector functions.
Retreive the index, values pairs from the series as an array. Each pair is [index, value]. This forces lazy evaluation to complete.
Returns an array of pairs that contains the series values. Each pair is a two element array that contains an index and a value.
Format the series for display as a string. This forces lazy evaluation to complete.
Generates and returns a string representation of the series.
Convert a series of values of different types to a series containing string values.
Optional formatting string for dates.
Numeral.js is used for number formatting. http://numeraljs.com/
Moment is used for date formatting. https://momentjs.com/docs/#/parsing/string-format/
Returns a new series values converted from values to strings.
Produces a new series with all string values truncated to the requested maximum length.
The maximum length of the string values after truncation.
Returns a new series with strings that are truncated to the specified maximum length.
Creates a new series by merging two input dataframes. The resulting series contains the union of value from the two input series. These are the unique combination of values in both series. This is basically a concatenation and then elimination of duplicates.
The other series to merge.
Optional user-defined selector function that selects the value to compare to determine distinctness.
Returns the union of the two series.
Partition a series into a new series of variable-length data windows where the divisions between the data chunks are defined by a user-provided comparer function.
Function that compares two adjacent data values and returns true if they should be in the same window.
Returns a new series, each value of which is a chunk of data from the original series.
Get the variance of number values in the series.
Returns the variance of the values in the series.
Filter the series using user-defined predicate function.
where
is an alias for Series.filter.
This is the same concept as the JavaScript function Array.filter
but filters a data series rather than an array.
Predicate function to filter values from the series. Returns true/truthy to keep elements, or false/falsy to omit elements.
Returns a new series containing only the values from the original series that matched the predicate.
Partition a series into a Series of data windows. Each value in the new series is a chunk of data from the original series.
The number of values to include in each data window.
Sets which side of the window the index comes from: start or end. Can be "start" or "end", defaults to "end".
Returns a new series, each value of which is a chunk (data window) of the original series.
Apply a new Index to the series.
Returns a new series with the specified Index attached.
Zip together multiple series to create a new series. Preserves the index of the first series.
User-defined zipper function that merges rows. It produces values for the new series based-on values from the input series.
Returns a single series merged from multiple input series.
Generated using TypeDoc
Interface that represents a series. A series contains an indexed sequence of values. A series indexed by time is a timeseries.